Novel Strategy for Three-Dimensional Fragment-Based Lead Discovery
Novel Strategy for Three-Dimensional Fragment-Based Lead Discovery
复制标题
基于三维片段的先导化合物发现的新策略
DOI：
10.1021/ci200003c
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发表时间：
2011-03
影响因子：
5.6
通讯作者：
Wang, Jian
中科院分区：
文献类型：
--
作者：
Yuan, Haoliang;Chen, Yadong;Lu, Tao;Ran, Ting;Liu, Haichun;Lu, Shuai;Tai, Wenting;Leng, Ying;Zhang, Weiwei;Wang, Jian
基于片段的药物设计(FBDD)被认为是一种很有前途的先导发现方法。然而，要使这一方法得到实际应用，还需要解决一些问题。因此，本工作提出了一种新的实用的三维铅发现策略。通过解构位于同一靶标活性部位的排列良好的已知抑制剂，可以产生不同的片段，这些片段的空间位置和取向保持在单独的相邻区域。这些三维片段在通过片段连接和融合构建新分子的过程中保持了原有的结合模式。均方根偏差(RMSD)值被用来评估最终化合物中各组分片段的构象变化，并以潜在的先导为主要标准。此外，基于两个相关的肿瘤靶点(CDK2和c-Met)，我们成功地验证了我们的策略，展示了我们的策略在促进针对某些药物靶点的先导发现方面的潜力。
Fragment-based drug design (FBDD) is considered a promising approach in lead discovery. However, for a practical application of this approach, problems remain to be solved. Hence, a novel practical strategy for three-dimensional lead discovery is presented in this work. Diverse fragments with spatial positions and orientations retained in separately adjacent regions were generated by deconstructing well-aligned known inhibitors in the same target active site. These three-dimensional fragments retained their original binding modes in the process of new molecule construction by fragment linking and merging. Root-mean-square deviation (rmsd) values were used to evaluate the conformational changes of the component fragments in the final compounds and to identify the potential leads as the main criteria. Furthermore, the successful validation of our strategy is presented on the basis of two relevant tumor targets (CDK2 and c-Met), demonstrating the potential of our strategy to facilitate lead discovery against some drug targets.
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影响因子：
7.3
作者：
E. Yue;C. Higley;Dimeo Susan;D. Carini;D. Nugiel;Carrie Benware;P. Benfield;C. Burton;S. Cox;R. Grafstrom;Diane M. Sharp;Lisa M Sisk;J. Boylan;J. Muckelbauer;A. Smallwood;Haiying Chen;Chong-Hwan Chang;S. P. Seitz;G. Trainor
通讯作者：
E. Yue;C. Higley;Dimeo Susan;D. Carini;D. Nugiel;Carrie Benware;P. Benfield;C. Burton;S. Cox;R. Grafstrom;Diane M. Sharp;Lisa M Sisk;J. Boylan;J. Muckelbauer;A. Smallwood;Haiying Chen;Chong-Hwan Chang;S. P. Seitz;G. Trainor
影响因子：
3.5
作者：
C. Verlinde;G. Rudenko;W. Hol
通讯作者：
C. Verlinde;G. Rudenko;W. Hol
影响因子：
2.7
作者：
Breault, GA;Ellston, RPA;Pease, JE
通讯作者：
Pease, JE
影响因子：
7.3
作者：
Andrew J. S. Knox;Trevor Price;M. Pawlak;Georgia Golfis;Christopher T Flood;D. Fayne;D. Williams;M. Meegan;David Lloyd
通讯作者：
Andrew J. S. Knox;Trevor Price;M. Pawlak;Georgia Golfis;Christopher T Flood;D. Fayne;D. Williams;M. Meegan;David Lloyd
影响因子：
7.3
作者：
Kolb, Peter;Caflisch, Amedeo
通讯作者：
Caflisch, Amedeo